exponential family
On Semiparametric Exponential Family Graphical Models
... We propose a new class of semiparametric exponential family graphical models for the anal- ysis of high dimensional mixed data. Different from the existing mixed graphical models, we allow the nodewise ...
59
Graphical Models via Univariate Exponential Family Distributions
... Undirected graphical models, or Markov networks, are a popular class of statistical mod- els, used in a wide variety of applications. Popular instances of this class include Gaussian graphical models and Ising models. In ...
35
Exponential family mixed membership models for soft?clustering of multivariate data
... The general case of mixed membership models, where quite general component distributions were allowed, has been outlined by Erosheva et al. (2004), however, details of how inference is to be performed are omitted; a ...
22
Estimation of P(X>Y) for the Positive Exponential Family of Distributions
... Constantine et al. (1986) derived UMVUE and MLE of P when X and Y follow gamma distributions with shape parameters to be integer-valued. Huang et al. (2012) generalized these results for the case when shape parameters ...
19
On a Generalization of the Positive Exponential Family of Distributions and the Estimation of Reliability Characteristics
... Example 1. This data set was originally reported in Schafft et al. (1987) (see also Ku- mar et al., 2017), represents hours to failure of 59 conductors of 400-micrometer length. All specimens ran to failure at a certain ...
21
Explaining and Generalizing Skip Gram through Exponential Family Principal Component Analysis
... We have presented an interpretation of the skip- gram model as exponential family principal com- ponents analysis—a form of matrix factorization— and, thus, related it to an older strain of work. Building ...
7
The odd generalized exponential family of distributions with applications
... exponential family. We study some structural properties of the new family including an expansion for its den- sity ...the family parameters. We fit three special models of the proposed ...
28
Parameter Uncertainty in Exponential Family Tail Estimation
... The analytically tractable examples of section 2 show that tail estimates may be very biased. In order to be able to treat more general cases, we develop in this section asymptotic formulas that can be used to ...
35
Sinuhe – Statistical Machine Translation using a Globally Trained Conditional Exponential Family Translation Model
... However, when defining the phrase-based sentence level transla- tion model, phrase overlaps are explicitly disal- lowed: The source sentence is segmented into dis- joint phrases, which a[r] ...
10
Bayesian Estimation of Reliability Function for A Changing Exponential Family Model under Different Loss Functions
... of exponential and poisson variables are investigated by Worsley (1986); Haccou, Meelis and Geer (1988); Estimation of shift point in a homogeneous poisson process studied by Jandhyala and Fotopolus (1999) and ...
6
Density Estimation in Infinite Dimensional Exponential Families
... being the cumulant generating function, and ( H , h·, ·i H ) a reproducing kernel Hilbert space (RKHS) (Aronszajn, 1950) with k as its reproducing kernel. While various generalizations are possible for different choices ...
59
One-Class SVMs Challenges in Audio Detection and Classification Applications
... Support vector machines (SVMs) have gained great attention and have been used extensively and successfully in the field of sounds (events) recognition. However, the extension of SVMs to real-world signal processing ...
14
GLM_slides_5_continuous_response.pdf
... On the other hand, lognormal distribution belongs to 2-parameter exponential family with natural parameters and natural statistics, respectively, given by. − 1 2 σ 2 ,[r] ...
39
Integer valued stochastic volatility
... The literature on time series of counts has put forward parameter-driven models, which do not consider a dynamic equation for the latent intensity parameter (Zeger, 1998; Davis et al., 1999, 2000; Hay and Pettitt, 2001; ...
44
BayesPy: Variational Bayesian Inference in Python
... BayesPy can be used to construct conjugate exponential family models. The documentation provides detailed examples of how to construct a variety of models, including principal component analysis models, ...
6
International Journal of Emerging Technology and Advanced Engineering
... designed procedures in broader applications, we derived the second-order lower bound of the Bayes risk for the product of k means of independent populations under the Bayesian framework. The trials of samplings are from ...
8
An introduction to differential geometry in econometrics
... curved exponential family is due to Efron (1975, 1978 & 1982) in a series of seminal papers which revived interest in the geometric aspects of statistical ...the exponential family class ...
45
GLM_slides_2_exp_family_print.pdf
... Lecture 2. Exponential Family of Distributions Score function.. binary, count).. The variance of Y depends on the mean...[r] ...
32
Characterizations of Exponentiated Distributions
... different method of estimations, J. Exponentiated exponential family: an ) alternative to gamma and Weibull distributions, Biometrical J., 43 , 117 130. Generalized exponential di[r] ...
8
Numerical Solutions of a System of ODEs Based on Lie Trotter and Strang Operator splitting Methods
... first-order exponential splitting method (or exponential Lie-Trotter splitting) and second order exponential splitting method (or exponential Strang splitting method ) for the Cauchy ...
5